In this paper we develop an original approach to evaluate the costs and benefits associated to a generic promotion program using an application to Bordeaux wines. The benefit is computed from the marginal impact of the collective reputation of the program on the individual reputation of its members. These different marginal impacts are estimated using detailed survey data about the image of Bordeaux wines in seven European countries. We find positive and significant spillover effects from the umbrella reputation (Bordeaux) that moreover increase with the individual reputation level of the wine. Controlling for the natural endogeneity of the collective reputation in this setup, we capture the important fact that this relationship is faced with marginal diminishing returns. These spillover effects, when significantly positive, vary from a minimum of 5% to a maximum of 15% of additional favorable quality opinions. We then show that some subregions are more likely to benefit from generic promotion programs, suggesting that fees should be established on a benefit-cost basis.

Accurate prognosis and prediction of a patient's current disease state is critical in an ICU. The use of vast amounts of digital medical information can help in predicting the best course of action for the diagnosis and treatment of patients. The proposed technique investigates the strength of using a combination of latent variable models (latent dirichlet allocation) and structured data to transform the information streams into potentially actionable knowledge. In this project, I use Apache Spark to predict mortality among ICU patients so that it can be used as an acuity surrogate to help physicians identify the patients in need of immediate care.

The aim of the experiment is to study elliptically polarized light using a Fresnel rhomb and to determine the ratio of semi major axis to the semi minor axis of the various elliptically polarised light forms for different angles of plane polarised incidence at the rhomb